most citedDocEnTr: An End-to-End Document Image Enhancement Transformer

2 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts

Giuseppe De Gregorio, Sanket Biswas, Mohamed Ali Souibgui +4

Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available…

cs.CV2022

A Generic Image Retrieval Method for Date Estimation of Historical Document Collections

Adrià Molina, Lluis Gomez, Oriol Ramos Terrades +1

Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to othe…

cs.CV20222 cited

DocEnTr: An End-to-End Document Image Enhancement Transformer

Mohamed Ali Souibgui, Sanket Biswas, Sana Khamekhem Jemni +4

Document images can be affected by many degradation scenarios, which cause recognition and processing difficulties. In this age of digitization, it is important to denoise them for…

cs.CV2021

Graph-based Deep Generative Modelling for Document Layout Generation

Sanket Biswas, Pau Riba, Josep Lladós +1

One of the major prerequisites for any deep learning approach is the availability of large-scale training data. When dealing with scanned document images in real world scenarios, t…

cs.CV20211 cited

DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis

Sanket Biswas, Pau Riba, Josep Lladós +1

Despite significant progress on current state-of-the-art image generation models, synthesis of document images containing multiple and complex object layouts is a challenging task.…